Top Senior Machine Learning Jobs in Huntsville, AL

As a Senior Machine Learning Engineer at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

Lead design, training, fine-tuning, and deployment of ML and generative models (LLMs, diffusion). Build scalable MLOps pipelines, vectorization and data ingestion, integrate models into microservices for low-latency inference, implement evaluation/alignment/bias-mitigation, optimize models (quantization, distillation), and mentor engineers while influencing the AI product roadmap.

Build and design backend services, AI agents, and machine learning models. Collaborate cross-functionally to deliver AI features and maintain code quality.

The Senior ML Data Scientist will develop machine learning models to detect fraud, manage the data science lifecycle, and collaborate with teams on strategies.

Design, build, and deploy production-grade AI/ML and LLM-based systems. Lead end-to-end ML lifecycle, implement RAG and embedding pipelines, establish MLOps best practices, mentor engineers, and collaborate with cross-functional teams to deliver scalable, responsible AI solutions.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The Lead Machine Learning Scientist will develop and implement ML strategies to enhance marketing and product capabilities, identify opportunities for growth using data, lead core model development, and improve marketing spend efficiency through insights and experimentation.

Design and operate production ML systems for large-scale streaming data, ensuring reliability and performance while collaborating with researchers to integrate models into distributed systems.

Lead design and delivery of scalable AI systems for autonomous threat detection and response. Build and productionize LLMs, graph reasoning engines, streaming feature pipelines, and orchestration frameworks. Own evaluation, reliability, and cross-functional collaboration while mentoring engineers and experimenting with RAG, tool-calling agents, and multi-modal models.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

Design, build, and deploy scalable ML models and pipelines to enhance a talent marketplace and GenAI solutions. Lead experimentation (A/B tests, statistical validation), improve production ML performance, ensure code and data quality, work with cross-functional teams, mentor junior engineers, and propose innovative AI-driven solutions aligned to business goals.

Lead technical roadmap and architecture for ML data infrastructure supporting petabyte-scale pipelines. Manage and mentor engineering team, design ingestion/transformation/serving systems, ensure data quality, lineage, governance, and collaborate with ML and infrastructure teams to deliver production-grade ML data pipelines and feature stores.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

As a Senior Machine Learning Engineer, you will design and maintain ML systems for content recommendations, search, and spam detection, while augmenting user experience and system performance.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

Lead development and productionization of large-scale ranking and personalization ML systems. Build data pipelines, features, and models (batch and real-time), collaborate cross-functionally, run experiments, and improve infrastructure for search, recommendation, and marketplace optimization.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Design, build, test, deploy, and maintain production AI capabilities (agents, workflows, models, MCP servers, APIs) across a SaaS dental platform. Train and operate ML models, implement RAG and vector DB solutions, use AI-assisted tools, collaborate in design and code reviews, and support production reliability and monitoring.

Design, optimize, and operate production LLM inference and training pipelines. Improve latency, throughput, and GPU utilization using techniques like batching, quantization, FlashAttention, and kernel-level profiling. Deploy and autoscale multiple models on shared GKE GPU clusters, consult with clients on performance and cost requirements, and carry prototypes to robust, scalable production services.

Design, develop, and deploy end-to-end AI/ML applications (RAG, chatbots, agentic workflows). Build scalable data pipelines, apply graph analytics, entity resolution, and NLP for risk scoring, anomaly detection, and investigative prioritization. Develop models, REST APIs, and deploy/manage solutions in AWS to support federal mission use cases.

Develop and scale reinforcement-learning systems that close the loop between automated labs and reward models. Build synthetic data engines and inference infrastructure for large-scale training, maintain evaluations of learned policies using proprietary experimental datasets, and address real-world challenges like experimental noise and expensive queries.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

The role involves developing and deploying machine learning models for forecasting within the Camus platform, requiring collaboration and technical depth in ML.